Genetic mutations are known to cause acute and chronic liver diseases, and are being increasingly recognized as drivers of phenotype severity. As a group, these diseases represent a substantial disease burden in the United States, and constitute a diagnostic challenge in the clinical evaluation of affected patients. In a Phase I Award, we developed the JAUNDICENEXT, a sequencing platform that combines short- and long-range PCRs to produce amplicons of target genes, the generation of patient-specific libraries, and sequencing by next-generation technologies to successfully identify mutations in subjects with inherited syndromes of intrahepatic cholestasis. Then, we began experiments to further improve the efficacy and scope of the sequencing platform to better meet the diagnostic needs of patients with genetic liver diseases. In preliminary studies for this application, we performed proof-of-principle experiments that demonstrated the feasibility and technical merit of an innovative sequencing platform using a simplified 2- step protocol that combines specific multiplexing chemistry coded for individual patients with an immediate sequencing by next-generation technology. Having demonstrated the technological merit of this newer platform, we propose to expand the gene coverage by creating the LIVERCHIP, a high-throughput sequencing platform that screens for mutations in 12 genes that manifest as pathologic jaundice, chronic liver injury, and cystic diseases of the liver, thus meeting the needs of a broader population. To this end, we propose three complementary aims to: 1) transition the JAUNDICENEXT to the LIVERCHIP as an expanded diagnostic tool, 2) bench-test the LIVERCHIP in patients with chronic inheritable liver diseases, and 3) to develop an analytical tool that optimizes mutation detection by the LIVERCHIP. Our experimental strategy will begin with the development and validation of a TruSeq multiplexing chemistry that enables the sequencing of 12 liver genes accurately in a 2-step assay. This will be followed by bench-testing the assay against a group of well-phenotype patients for each one of the target diseases. Last, we will develop a browser that will decrease the time required for the analysis of the nucleotide readout, thus decreasing the time-to-diagnosis. Our ultimate goal is to positively impact liver-based diagnostics by producing an assay that is accurate, requires short analytical time, and at much lower cost than currently available tests. These features will make the end-product user friendly in the clinical setting and increase its marketability.